Advances in Public Health Statistics and Data Analytics
Buch in deiner Nähe kaufen
Beschreibung
This book presents the most advanced Public Health Statistical modeling and data analytics in essential component in evidence-based public health decision. Modeling such as Poisson Regression, Joinpoint Regression, SIRD Model and Game Theory in Public Health and Medical Studies.
Advances in Public Health Statistics and Data Analytics is an essential component in evidence-based public health decision-making. To promote the research and development in public health statistics, this book is contributed from the leadership team at the Applied Public Health Statistics (APHS) Section from the American Public Health Association(APHA).
The primary aim of this book is to stimulate research, foster collaboration among statistical and public health researchers, and provide valuable opportunities for further academic and professional interactions. As a timely and authoritative resource, it serves as a reference for professionals, researchers, and graduate students in public health research and applications. The latest advancements presented in this volume are invaluable for both practitioners and academics seeking to navigate the evolving landscape of public health statistical science and data analytics.
This book presents the most advanced Public Health Statistical modeling and data analytics in essential component in evidence-based public health decision. Modeling such as Poisson Regression, Joinpoint Regression, SIRD Model and Game Theory in Public Health and Medical Studies.
Advances in Public Health Statistics and Data Analytics is an essential component in evidence-based public health decision-making. To promote the research and development in public health statistics, this book is contributed from the leadership team at the Applied Public Health Statistics (APHS) Section from the American Public Health Association(APHA).
The primary aim of this book is to stimulate research, foster collaboration among statistical and public health researchers, and provide valuable opportunities for further academic and professional interactions. As a timely and authoritative resource, it serves as a reference for professionals, researchers, and graduate students in public health research and applications. The latest advancements presented in this volume are invaluable for both practitioners and academics seeking to navigate the evolving landscape of public health statistical science and data analytics.
Equip understanding of key concepts in current advances in public health statistics and data analysis Public Health disease modeling for understanding infectious disease dynamics, such as COVID-19, Malaria, etc Advance applications in statistical and biostatistical method, algorithms to real-world datasets
Autor*in
Ding-Geng Chen
Themen in »Advances in Public Health Statistics and Data Analytics«
Causal effect estimation hierarchical model multi-level modeling longitudinal data analysis randomized trials data integration classification random forest multiple imputation machine learning big data missing data Poisson regression prevalence ratio time-dependent covariates